Source code for botorch.models.utils.gpytorch_modules

#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.

from typing import Optional

import torch
from gpytorch.constraints.constraints import GreaterThan
from gpytorch.kernels import MaternKernel, ScaleKernel
from gpytorch.likelihoods.gaussian_likelihood import GaussianLikelihood
from gpytorch.priors.torch_priors import GammaPrior


[docs] def get_matern_kernel_with_gamma_prior( ard_num_dims: int, batch_shape: Optional[torch.Size] = None ) -> ScaleKernel: r"""Constructs the Scale-Matern kernel that is used by default by several models. This uses a Gamma(3.0, 6.0) prior for the lengthscale and a Gamma(2.0, 0.15) prior for the output scale. """ return ScaleKernel( base_kernel=MaternKernel( nu=2.5, ard_num_dims=ard_num_dims, batch_shape=batch_shape, lengthscale_prior=GammaPrior(3.0, 6.0), ), batch_shape=batch_shape, outputscale_prior=GammaPrior(2.0, 0.15), )
[docs] def get_gaussian_likelihood_with_gamma_prior( batch_shape: Optional[torch.Size] = None, ) -> GaussianLikelihood: r"""Constructs the GaussianLikelihood that is used by default by several models. This uses a Gamma(1.1, 0.05) prior and constrains the noise level to be greater than MIN_INFERRED_NOISE_LEVEL (=1e-4). """ batch_shape = torch.Size() if batch_shape is None else batch_shape noise_prior = GammaPrior(1.1, 0.05) noise_prior_mode = (noise_prior.concentration - 1) / noise_prior.rate return GaussianLikelihood( noise_prior=noise_prior, batch_shape=batch_shape, noise_constraint=GreaterThan( MIN_INFERRED_NOISE_LEVEL, transform=None, initial_value=noise_prior_mode, ), )